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Record W7135639855

Informed Consent (Comparative Study)

2018· dissertation· cs· W7135639855 on OpenAlexaboutno aff
Jakub Franta

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2018
Typedissertation
Languagecs
FieldMedicine
TopicPatient Dignity and Privacy
Canadian institutionsnot available
Fundersnot available
KeywordsInformed consentPaternalismSubject (documents)CzechAutonomyBasic law
DOInot available

Abstract

fetched live from OpenAlex

Informed consent is one of the most discussed issues of medical law. This thesis tries to contribute to the discussion through a comparative study between Czech law and Canadian law (the common law part of Canadian law), focusing on the basic components of the subject matter. The thesis is divided into six parts. The first one deals with information disclosure and consent to treatment in the paternalistic model and the participatory model of a doctor-patient relationship. The second part provides an overview of relevant Czech and Canadian legal sources and also of key milestones in the development of informed consent in both countries. The third part of the thesis discusses the concept of informed consent. The fourth part is focused on the disclosure - its content and scope, form and other related aspects. The fifth part of the thesis deals with the consent itself - its elements, the withdrawal of consent and the refusal to give consent. Finally, the sixth part deals with the specifics of minors. With regard to the basic features of informed consent, it can be clearly stated that the compared legal systems are fundamentally the same. Differences can be seen only when analysing the subject matter into very great detail and those differences are usually various technicalities (e.g. determination of...

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.290
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.052
GPT teacher head0.343
Teacher spread0.291 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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